738 Approach for Detecting Rapidly Developing Convective Clouds with "HIMAWARI-8"

Wednesday, 13 January 2016
Yasuhiko Sumida, Japanese Meteorological Agency, Madison, WI; and H. Seko, A. Hashimoto, T. J. Schmit, A. Heidinger, and W. Straka III

The Japan Meteorological Agency (JMA) began operations with HIMAWARI-8 on July 7, 2015. The satellite carries a state-of-art visible/infrared radiometer, Advanced Himawari Imager (AHI), which acquires multi-spectral images very frequently (10 minute full disk imagery, 2.5 minute Regional imagery). JMA takes advantage of this rapid refresh data to provide a product that detects the areas of rapidly developing cumulus clouds. This product is estimated by cloud surface conditions and time differences of brightness temperatures. However, there is a limit to accurately detect the developing cumulous using only surface data. Currently, this product utilizes only two bands (1 infrared band (10.4 μm) and 1 visible band (0.64 μm)), and does not exploit the wide range of channels available on AHI for convective cloud detection and characterization.

The multi-spectral and high frequent satellite data will be used in the estimation of the cloud microphysics, such as cloud glaciation and cloud effective radius. Because the cloud microphysics are affected by the development of convective clouds, the multi-spectral and high frequent satellite data can be used as the precursor of the development of the convections. Namely, strong updrafts do not allow sufficient time in which cloud particles grow in rapidly developing clouds, and the convective clouds become brighter due to the greater component of small cloud particles at the cloud top.

This presentation introduces a multi-dimensional bin-microphysics model, which employs various parameters including ice particle mass and aspect ratio, calculates cloud particles and other water substances in the developing convective clouds. This model will be used to investigate the relations between developing speed of convective clouds and the presence of small cloud particles. The simulate AHI data will be produced from the bin-microphysics model data through a radiative transfer model. We are planning to compare the simulated AHI data to the observed AHI data as well as the derived cloud microphysical parameters from the AHI data to the cloud microphysical parameters in the model.

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